Empirical Analysis of Private Investments: The Case of Pakistan

Transcription

1 2011 International Conference on Sociality and Economics Development IPEDR vol.10 (2011) (2011) IACSIT Press, Singapore Empirical Analysis of Private Investments: The Case of Pakistan Dr. Asma Salman 1 1 Fatima Jinnah Women University, Rawalpindi, Pakistan Assistant Professor at the Department of Business Administration Abstract. Foreign Private Investments include the direct investments and portfolio investments in a particular country. Investments in any country have been linked with the growth terms of the host country. Pakistan is no exception. 24 year secondary data has been used to analyze the impact of foreign private investments on the balance of trade, capital and financial account, and economic growth (GDP) in Pakistan. Independent ADF Test statistic and Granger causality tests have been used through Eviews to generate some results. Keywords: ADF Test Statistic, Eviews, Private Investments, ARIMA 1. Introduction Foreign Private Investments could play a huge role in the economic development of a country, specially for a developing country like Pakistan. Foreign Direct Investments and Portfolio Investments form a part of the Private Investments in a country. Post industrialization period, Pakistan has seen stock market capitalization mostly during Pakistan has been through a rollercoaster ride as far as the political scenario is concerned. Since investment regimes are often backed by a political scenario, the same upheaval can be seen in Investments scenario and trade balances (imbalances) of Pakistan. The Political and Legal framework can create opportunities for the foreign investors or lead them to fly away. The most fitting example would be of the Asian financial Crisis, which saw capital flying away from the country and it also showed quite clearly the troubles entailed by Foreign Private Investments for the Host country. Foreign capital flows bring technological knowhow, economic growth, decrease in unemployment and increase in the Purchase power parity of the consumers of the host country is well documented in the Literature. Although Pakistan has witnessed a recent increase in the private investments but the long term affects (positive) are yet to be materialised. Foreign Private Investments may also have negative affects in a country, and the resultant growth may not be at par with the loss incurred through the capital and financial account balances (Salman, 2010). Available literature also suggests that Direct Investment is more stable then the Portfolio Investments, since the latter are more volatile. A healthy mix of both coupled with the right policies may be the answer. Extensive literature is available for the Direct Investments as compared to the Private Investments the data of which is only available after 1986 for Pakistan. Empirical analysis of Private Investments with other economic variables, I want to add to the existing literature of capital flows. The impact on foreign private investments through different variables has been analyzed with the view that it fosters economic growth and vows to find out the negative effect. 2. Empirical Analysis 2.1. Model Framework and Data Sources 1 Corresponding author. Tel.: address: asmasalman@fjwu.edu.pk 546

2 All the possible variables are quoted in the equation. Then, a regression equation based on the analysis of D.W (Durban Watson Statistic), AIC (Akaike Information Criterion) and SC (Schwarz Criterion) is fitted. This research will select indicators affecting the Foreign Private Investments from 1986 to 2009 to establish a model. FPI, KA, BOT and GDP represent foreign portfolio investment account, capital and financial account balance, balance of trade and gross domestic product. The sample is from year 1986 to The data is in Million ($). In Table V, sample statistics for each of these variables is presented. The related data is taken from Pakistan Handbook of Statistics, Board of Investments and The World Bank. The original model is: FPI = β0 +β1 KA +β2 BOT +β3 GDP +μ (1) 2.2. ADF-Test Statistic The Augmented Dickey Fuller Test Statistic is being used independently on each of the variables; to examine the null hypothesis of an autoregressive integrated moving average ARIMA (p, 1, 0) process against the stationary ARIMA (p +1, 0, 0) alternative. Dickey and Fuller (1979) derived the limiting distribution of the ADF test. The testing procedure for the ADF test is the same as for the Dickey Fuller test but it is applied to the model; Where α is a constant, β the coefficient on a time trend and p the lag order of the autoregressive process. Imposing the constraints α = 0 and β = 0 corresponds to modelling a random walk and using the constraint β = 0 corresponds to modelling a random walk with a drift. The unit root test is then carried out under the null hypothesis γ = 0 against the alternative hypothesis of γ < 0. The results suggest that each of the economic variables have a unit root in their first order lag differences except FPI and BOT, which are differenced at second and fourth order respectively. Using E views the following regression equation has been analyzed. FPI = β KA BOT GDP (2) Variable Regression Coefficient Std. Error Prob. BOT GDP KA C R-squared Mean dependent var Adjusted R- squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter Durbin-Watson stat F-statistic Prob(F-statistic) Table 1: Regression Results The negative sign of BOT suggest that with the private investments increasing there has been a decrease in the trade balance for Pakistan, meaning thereby that the imports have been exceeding. Trade balance consists of exports and imports which both play a dominant role in the determination of the current account balance. Favorable balance of trade means exports are greater than imports and it always supports the current account balance. Negative balance of trade causes a current account deficit. With the private investments entering Pakistan both the capital and financial account and the gross domestic product have been increasing albeit at a very slow rate. It gives us a clue that foreign ownership of securities in Pakistan deteriorates the 547

3 trade balance and the improvement is done through the financial account thus engaging Pakistan into a vicious circle. Residual Plots for Foreign Private Investments: Normal probability plot of the residual indicates whether the data is normally distributed, outliers exist in the data, and other variables are influencing the predictor. In our model, no evidence of abnormality (not a straight line), outliers (a point far away from the line), skewness (curve in the tails) or unidentified variables (changing slope) are found. Figure Granger Causality Test The test for Granger causality works by first doing a regression of ΔY on lagged values of ΔY. Once the set of significant lagged values for ΔY is found, the regression is augmented with lagged levels of ΔX. Any particular lagged value of ΔX is retained in the regression if it is significant according to a t-test or F-test. Then the null hypothesis of no Granger causality is accepted if and only if no lagged values of ΔX have been retained in the regression. Pairwise Granger Causality Tests Lags: 2 3. Conclusion Null Hypothesis: Obs F-Statistic Prob. GDP does not Granger Cause FPI FPI does not Granger Cause GDP KA does not Granger Cause FPI FPI does not Granger Cause KA BOT does not Granger Cause FPI FPI does not Granger Cause BOT KA does not Granger Cause GDP GDP does not Granger Cause KA BOT does not Granger Cause GDP GDP does not Granger Cause BOT BOT does not Granger Cause KA KA does not Granger Cause BOT Table II Granger Causality Test From the analysis it has been confirmed that the private investments affect the explained variables allot. The model fits well, and the negative relation of FPI and BOT has come into picture. The results are not extinctive and a positive relationship for Foreign Private Investment with the economic variables by Granger 548

4 causality test could not be generated. This may be because of the multiple deficits in Trade Balances. The reason could be that because the foreign private investment is very volatile in nature and since the political risks and the trade risks have been increased considerably post 9/11 era. Earlier work done by (Salman and Hui 2009) also suggested the negative impact of foreign direct investments on the current account balance. And through a more extensive perspective this stance has again been put forward through this research that the increase in private investments is decreasing the BOT for Pakistan and the growth also has been at a slow rate. The Trade imbalances have been a core issue for Pakistan, further research can be carried out in favor of the same with different indicators such as exchange rate, equity and domestic savings. 4. References [1] Salman. A and X.F Hui, FDI in Pakistan: Impact on GNP and Capital Financial Account, In proceedings of 2009 ICFTE, pp [2] Khan, AH, FDI in Pakistan: Policies and Trends, The Pakistan Development Review, 36 (4), part II, 1997 [3] Mencinger, J., The Addiction with FDI and current account balance, Working Paper No.16/2008, 2008 [4] Gulzar, S and X.F.Hui, Thirty years of chronic current account deficit , The case of current account deficit : The case of Pakistan, J. Harbin Inst. Technol., 14: , 2006 [5] Auerbach, Alan., The cost of capital and investment in developing countries, PRE Working Papers No.410, The World Bank, 1990 [6] Yang Liuyong, Zou Yanping, Empirical Analysis of the Impact of FDI on China s Balance of Payments, / IEEE, 2007 [7] Love, James. And Francisco Lage- Hidalgo., Analyzing The Determinants of US Direct Investment in Mexico, Applied Economics 32 (10), 2000 [8] Gallaghar.P.Kevin, Zarsky Lyuba., Sustainable Industrial Development. The performance of Mexico s FDI- led integration strategy, Global Development and Environment Institute. Fletcher School of Law and Diplomacy. Tufts University, Feburary [9] Iqbal, Javed, Stock Market in Pakistan: An Overview Online at MPRA Paper No [10] Heij et al. (2004) Linear Time Series Models for NonStationary data [11] Dickey, D.A. & Fuller, W.A. Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association. 1979, 74 : 427~431 [12] Granger, C.W.J. Some Properties of Time Series and Their Use in Econometric Model Specification. Journal of Econometrics. 1981, 16 : pp 121~130 [13] Handbook of Statistics on Pakistan Economy 2010, Published by State Bank of Pakistan. Chapter No 1.3, 7, , 7.12, and , :334~467 Null Hypothesis: KA has a unit root Lag Length: 0 (Automatic based on SIC, MAXLAG=5) statistic values: 1% level Null Hypothesis: FPI has a unit root Lag Length: 1 (Automatic based on SIC, MAXLAG=5) statistic values: 1% level % level % level Variable Coefficient Std. Error KA(-1) C % level % level Variable Coefficient Std. Error FPI(-1) D(FPI(-1)) C

5 Null Hypothesis: BOT has a unit root Lag Length: 4 (Automatic based on SIC, MAXLAG=5) statistic values: 1% level % level % level Variable Coefficient Std. Error BOT(-1) )) )) )) )) Null Hypothesis: GDP has a unit root Lag Length: 0 (Automatic based on SIC, MAXLAG=5) statistic values: 1% level % level % level Variable Coefficient Std. Error GDP(-1) C C Table III-IV ADF-TEST Statistic Results Years KA BoT FPI GDP , , , , , , , , , , , ,433 YEARS BOT FPI GDP KA , , , , , , , , , , , , Table VII Variable Data: source (World Bank, Handbook of Statistics; Pakistan) 550